CN117462314B - Damping adjustment method, damping adjustment device, intelligent artificial limb, intelligent artificial terminal and storage medium - Google Patents
Damping adjustment method, damping adjustment device, intelligent artificial limb, intelligent artificial terminal and storage medium Download PDFInfo
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- CN117462314B CN117462314B CN202311484583.5A CN202311484583A CN117462314B CN 117462314 B CN117462314 B CN 117462314B CN 202311484583 A CN202311484583 A CN 202311484583A CN 117462314 B CN117462314 B CN 117462314B
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Classifications
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- A61F—FILTERS IMPLANTABLE INTO BLOOD VESSELS; PROSTHESES; DEVICES PROVIDING PATENCY TO, OR PREVENTING COLLAPSING OF, TUBULAR STRUCTURES OF THE BODY, e.g. STENTS; ORTHOPAEDIC, NURSING OR CONTRACEPTIVE DEVICES; FOMENTATION; TREATMENT OR PROTECTION OF EYES OR EARS; BANDAGES, DRESSINGS OR ABSORBENT PADS; FIRST-AID KITS
- A61F2/00—Filters implantable into blood vessels; Prostheses, i.e. artificial substitutes or replacements for parts of the body; Appliances for connecting them with the body; Devices providing patency to, or preventing collapsing of, tubular structures of the body, e.g. stents
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- A61F2/00—Filters implantable into blood vessels; Prostheses, i.e. artificial substitutes or replacements for parts of the body; Appliances for connecting them with the body; Devices providing patency to, or preventing collapsing of, tubular structures of the body, e.g. stents
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Abstract
The invention discloses a damping adjustment method, a damping adjustment device, an intelligent artificial limb, a terminal and a storage medium. Judging the current movement mode of the intelligent artificial limb wearer; determining initial damping and damping intervals corresponding to knee joints of the intelligent artificial limb according to the motion mode; and acquiring the movement speed of the intelligent artificial limb at intervals of preset time, and adjusting the current damping in the damping interval according to the movement speed. The invention presets damping and damping intervals of different motion modes, and adjusts initial damping and damping intervals corresponding to knee joints of the intelligent artificial limb based on the motion modes of a wearer when the intelligent artificial limb is applied. In the movement process of the wearer, the invention can also adjust the current damping based on the movement speed in the damping interval, thereby better meeting the movement requirements of the intelligent artificial limb wearer in different movement modes. The intelligent artificial limb damper solves the problem that the damper of the intelligent artificial limb in the prior art adopts preset parameters, and is difficult to adapt to the movement requirements of a wearer in different movement modes.
Description
Technical Field
The invention relates to the field of intelligent artificial limb control, in particular to a damping adjustment method and device, an intelligent artificial limb, a terminal and a storage medium.
Background
The limb disabilities often affect the daily life of people, and reduce their quality of life while also bringing a heavy burden to caring their families and society. Since the current medical level is not capable of regenerating the limb, the installation of prostheses for these amputees is also an important means of compensating for the defective limb. The intelligent knee joint of the intelligent artificial limb in the prior art can adjust damping and pressure through the damper, and the damper can control the speed and the strength of the joint in the movement process. The technician or physician will adjust the damper settings according to the needs of the intelligent prosthesis wearer to ensure that the joint provides the proper resistance to movement. However, the prosthesis wearer may be in various different exercise modes in daily life, such as walking, running, riding, and the damper of the intelligent prosthesis adopts pre-adjusted parameters, so that it is difficult to adapt to the exercise requirements of the various different exercise modes.
Accordingly, there is a need for improvement and development in the art.
Disclosure of Invention
The invention aims to solve the technical problems that aiming at the defects in the prior art, a damping adjustment method, a damping adjustment device, an intelligent artificial limb, a terminal and a storage medium are provided, and aims to solve the problems that in the prior art, a damper of the intelligent artificial limb adopts preset parameters, and the damper is difficult to adapt to the movement requirements of different movement modes in daily life of a wearer.
The technical scheme adopted by the invention for solving the problems is as follows:
in a first aspect, an embodiment of the present invention provides a damping adjustment method, including:
judging the current movement mode of the wearer of the intelligent artificial limb;
determining initial damping and damping intervals corresponding to knee joints of the intelligent artificial limb according to the motion mode;
and acquiring the movement speed corresponding to the intelligent artificial limb at intervals of preset time, and adjusting the current damping in the damping interval according to the movement speed.
In one embodiment, the determining the current movement pattern of the wearer of the intelligent prosthesis includes:
acquiring detection data of the knee joint of the intelligent artificial limb, converting the detection data into waveform data, and determining periodic distribution rule information corresponding to the detection data according to the waveform data;
obtaining a motion pattern database, wherein the motion pattern database comprises a plurality of reference motion patterns, and each reference motion pattern is provided with a corresponding periodic distribution rule label;
and matching the periodic distribution rule information with the motion pattern database, and determining the motion pattern according to a matching result.
In one embodiment, the initial damping and the damping interval are both preset; the initial damping comprises bending damping, the damping interval comprises a bending damping interval corresponding to the bending damping, and the setting method of the bending damping and the bending damping interval comprises the following steps:
acquiring a plurality of human body moving images continuously acquired in the motion mode, and inputting each human body moving image into a skeleton recognition algorithm to obtain skeleton sequence data;
identifying human body gravity center points in the skeleton sequence data, and determining human body gravity center change characteristics according to the identified human body gravity center points;
and determining the bending damping and the bending damping interval according to the gravity center change characteristics of the human body.
In one embodiment, the initial damping further includes an extension damping, the damping section further includes an extension damping section corresponding to the extension damping, and the setting method of the extension damping and the extension damping section includes:
identifying knee joint points in the skeleton sequence data, and determining knee joint change characteristics according to each identified knee joint point;
and determining the stretching damping and the stretching damping interval according to the knee joint change characteristics.
In one embodiment, the adjusting the current damping in the damping interval according to the movement speed includes:
acquiring a reference speed interval corresponding to the movement mode, and judging whether to change the movement mode according to the movement speed and the reference speed interval;
if not, adjusting the current damping in the damping interval according to the movement speed;
if yes, the step of judging the current movement mode of the wearer of the intelligent artificial limb is executed again.
In one embodiment, if not, adjusting the current damping in the damping interval according to the movement speed includes:
if not, acquiring the historical movement speed recorded in the previous time;
determining the speed variation value according to the difference value of the historical movement speed and the movement speed;
and adjusting the current damping in the damping interval according to the speed variation value.
In one embodiment, if not, adjusting the current damping in the damping interval according to the movement speed includes:
acquiring a preset corresponding relation curve, wherein the corresponding relation curve is used for reflecting the corresponding relation between the speed and the damping value in the damping interval;
And determining target damping on the corresponding relation curve according to the movement speed, and adjusting the current damping according to the target damping.
In a second aspect, an embodiment of the present invention further provides a damping adjustment device, including:
the mode judging module is used for judging the current movement mode of the wearer of the intelligent artificial limb;
the damping determining module is used for determining initial damping and damping intervals corresponding to the knee joint of the intelligent artificial limb according to the motion mode;
the damping adjustment module is used for acquiring the movement speed corresponding to the intelligent artificial limb at intervals of preset time, and adjusting the current damping in the damping interval according to the movement speed.
In one embodiment, the initial damping and the damping interval are both preset; the initial damping includes bending damping, the damping interval includes a bending damping interval corresponding to the bending damping, and the device further includes:
the image analysis module is used for acquiring a plurality of human body moving images continuously acquired in the motion mode, and inputting each human body moving image into a skeleton recognition algorithm to obtain skeleton sequence data;
the gravity center identification module is used for identifying the gravity center points of the human body in the skeleton sequence data and determining the gravity center change characteristics of the human body according to the identified gravity center points of the human body;
The first determining module is used for determining the bending damping and the bending damping interval according to the gravity center change characteristics of the human body.
In one embodiment, the initial damping further comprises an extension damping, the damping interval further comprises an extension damping interval corresponding to the extension damping, and the apparatus further comprises:
the knee joint identification module is used for identifying knee joint points in the skeleton sequence data and determining knee joint change characteristics according to the identified knee joint points;
and the second determining module is used for determining the stretching damping and the stretching damping interval according to the knee joint change characteristics.
In one embodiment, the damping adjustment module includes:
the speed analysis unit is used for acquiring a reference speed interval corresponding to the movement mode and judging whether to change the movement mode according to the movement speed and the reference speed interval;
the damping adjusting unit is used for adjusting the current damping in the damping interval according to the movement speed if not;
and the mode replacing unit is used for re-executing the step of judging the current movement mode of the wearer of the intelligent artificial limb if the intelligent artificial limb is in the current movement mode.
In a third aspect, embodiments of the present invention further provide a smart prosthesis comprising a knee joint and a damping adjustment device as described in any one of the above; the knee joint comprises an angle sensor and an inertial sensor, and the angle sensor and the inertial sensor are used for acquiring detection data of the knee joint.
In a fourth aspect, an embodiment of the present invention further provides a terminal, where the terminal includes a memory and more than one processor; the memory stores more than one program; the program contains instructions for executing the damping adjustment method according to any one of the above; the processor is configured to execute the program.
In a fifth aspect, embodiments of the present invention further provide a computer readable storage medium having stored thereon a plurality of instructions adapted to be loaded and executed by a processor to implement the steps of any of the above-described damping adjustment methods.
The invention has the beneficial effects that: according to the embodiment of the invention, the damping and the damping intervals of different motion modes are preset, and the initial damping and the damping intervals corresponding to the knee joint of the intelligent artificial limb are adjusted based on the motion modes of the wearer in practical application. In the movement process of the wearer, the invention can also adjust the current damping in the damping interval based on the movement speed of the wearer, thereby better meeting the movement requirements of the wearer in different movement modes when wearing the intelligent artificial limb. The intelligent artificial limb damper solves the problem that the damper of the intelligent artificial limb in the prior art adopts preset parameters, and is difficult to adapt to the movement requirements of different movement modes in daily life of a wearer.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments described in the present invention, and other drawings may be obtained according to the drawings without inventive effort to those skilled in the art.
Fig. 1 is a flow chart of a damping adjustment method according to an embodiment of the present invention.
Fig. 2 is a schematic block diagram of a damping adjustment device according to an embodiment of the present invention.
Fig. 3 is a schematic structural view of an intelligent artificial limb according to an embodiment of the present invention.
Fig. 4 is a schematic block diagram of a terminal according to an embodiment of the present invention.
Detailed Description
The invention discloses a damping adjustment method, a damping adjustment device, an intelligent artificial limb, a terminal and a storage medium, and further detailed description of the invention is provided below with reference to the accompanying drawings and examples in order to make the purposes, the technical schemes and the effects of the invention clearer and more definite. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
As used herein, the singular forms "a", "an", "the" and "the" are intended to include the plural forms as well, unless expressly stated otherwise, as understood by those skilled in the art. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. It will be understood that when an element is referred to as being "connected" or "coupled" to another element, it can be directly connected or coupled to the other element or intervening elements may also be present. Further, "connected" or "coupled" as used herein may include wirelessly connected or wirelessly coupled. The term "and/or" as used herein includes all or any element and all combination of one or more of the associated listed items.
It will be understood by those skilled in the art that all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs unless defined otherwise. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
In view of the above-mentioned drawbacks of the prior art, the present invention provides a damping adjustment method by determining a current movement pattern of a wearer of an intelligent prosthesis; determining initial damping and damping intervals corresponding to knee joints of the intelligent artificial limb according to the motion mode; and acquiring the movement speed corresponding to the intelligent artificial limb at intervals of preset time, and adjusting the current damping in the damping interval according to the movement speed. According to the invention, the damping and the damping intervals of different motion modes are preset, and the initial damping and the damping intervals corresponding to the knee joint of the intelligent artificial limb are adjusted based on the motion modes of the wearer in practical application. In the movement process of the wearer, the invention can also adjust the current damping in the damping interval based on the movement speed of the wearer, thereby better meeting the movement requirements of the wearer in different movement modes when wearing the intelligent artificial limb. The intelligent artificial limb damper solves the problem that the damper of the intelligent artificial limb in the prior art adopts preset parameters, and is difficult to adapt to the movement requirements of different movement modes in daily life of a wearer.
As shown in fig. 1, the method includes:
and step S100, judging the current movement mode of the wearer of the intelligent artificial limb.
Specifically, because the movement requirements of the wearer on the intelligent artificial knee joint are different in different movement modes, the damping and damping intervals of the knee joint corresponding to the different movement modes are preset in the embodiment. In an actual application scene, firstly, what motion mode the wearer of the intelligent artificial limb is in is judged.
In one implementation, the determining the current movement pattern of the wearer of the intelligent prosthesis includes:
acquiring detection data of the knee joint of the intelligent artificial limb, converting the detection data into waveform data, and determining periodic distribution rule information corresponding to the detection data according to the waveform data;
obtaining a motion pattern database, wherein the motion pattern database comprises a plurality of reference motion patterns, and each reference motion pattern is provided with a corresponding periodic distribution rule label;
and matching the periodic distribution rule information with the motion pattern database, and determining the motion pattern according to a matching result.
Specifically, the present embodiment provides several sensors in advance in the intelligent prosthetic knee joint, including, for example, an angle sensor and an inertial sensor. These sensors may detect movement data of the intelligent prosthesis, such as data including angle, velocity, acceleration, etc. of the knee joint. In order to better analyze the information contained in the detection data, the detection data is first converted into waveform data, the abscissa of which corresponds to the time axis and the ordinate corresponds to the detection value. The waveform of the detection data will show different periodic distribution rules in different motion modes, so that the embodiment can extract relevant periodic distribution rule information according to the waveform data. In order to improve the efficiency of motion pattern recognition, the embodiment pre-constructs a motion pattern database, and the database stores a plurality of reference motion patterns obtained by pre-analysis and a periodic distribution rule of each reference motion pattern. In an actual application scene, a corresponding reference motion pattern is matched in a motion pattern database according to the periodic distribution rule information obtained at present, and the motion pattern of the wearer at present can be obtained according to the matching result.
In another implementation, the determining the current movement pattern of the wearer of the intelligent prosthesis includes:
acquiring a plurality of detection data of the intelligent knee joint, and respectively determining corresponding periodic distribution rule information according to each detection data;
acquiring feature point sets corresponding to the detection data respectively, and determining joint distribution rule information according to the feature point sets, wherein the joint distribution rule information is used for reflecting the relevance of feature point distribution between at least two feature point sets;
and determining the current movement mode of the intelligent artificial limb according to the periodic distribution rule information and the joint distribution rule information.
For each detection data, it will show different periodic distribution rules in different motion modes. Therefore, in this embodiment, each detection data is analyzed separately, and the periodic distribution rule of the detection data is extracted. In the same exercise mode, various detected data fluctuations have certain relevance, for example, in a running mode, the minimum acceleration is generated when the bending angle is maximized (corresponding to the leg lifting action during running). Therefore, in order to fully mine information in various detection data, the embodiment not only carries out independent analysis on various detection data, but also carries out joint analysis on various detection data in a summarization way. In order to reduce the time cost of data analysis, the embodiment firstly performs feature point extraction on various detection data to obtain a feature point set (including a plurality of feature points and information such as time points and attribute categories corresponding to the feature points). And then comparing and analyzing different characteristic point sets to summarize the relevance among the characteristic point sets, and obtaining the joint distribution rule information. The periodic distribution rule information can reflect the respective data characteristics of different acquired data, and the joint distribution rule information can reflect the associated characteristics among different acquired data, and the characteristics can be mutually verified, so that the mode identification can be cooperatively carried out, and a more accurate and reliable mode identification result is obtained.
And step 200, determining initial damping and damping intervals corresponding to the knee joint of the intelligent artificial limb according to the motion mode.
In particular, since the wearer's movement needs for the smart prosthetic knee joint are different in different movement patterns, the present embodiment determines the initial damping of the smart prosthetic knee joint and the fluctuation range (i.e., damping interval) of the initial damping according to the currently recognized movement pattern.
In one implementation, the initial damping and the damping interval are both preset; the initial damping comprises bending damping, the damping interval comprises a bending damping interval corresponding to the bending damping, and the setting method of the bending damping and the bending damping interval comprises the following steps:
acquiring a plurality of human body moving images continuously acquired in the motion mode, and inputting each human body moving image into a skeleton recognition algorithm to obtain skeleton sequence data;
identifying human body gravity center points in the skeleton sequence data, and determining human body gravity center change characteristics according to the identified human body gravity center points;
and determining the bending damping and the bending damping interval according to the gravity center change characteristics of the human body.
Specifically, the initial damping preset for different motion modes in this embodiment actually includes multiple types of damping, one of which is bending damping, and the bending damping is used to provide a certain supporting force for the intelligent artificial limb when the intelligent artificial limb falls to the ground during the motion process. The bending damping of different motion modes and the setting method principle of the bending damping interval are the same, and one motion mode is taken as an example: first, continuously acquiring the moving images of the human body in the moving mode, for example, the moving mode is a running mode, and the moving images of the user A during running can be continuously acquired. And then recognizing skeleton parts in each human body moving image through a pre-constructed skeleton recognition algorithm, and generating skeleton sequence data through the recognized skeleton parts under different time steps. And then, recognizing the gravity center of the human body in the skeleton sequence data, connecting all the recognized gravity center of the human body to obtain a first change curve of the gravity center of the human body, and extracting the characteristics of the first change curve to obtain the gravity center change characteristics of the human body. The gravity center change characteristic of the human body can reflect the requirement of the human body on balance/support in the movement mode, so that the bending damping and the bending damping interval in the movement mode can be set by taking the gravity center change characteristic of the human body as a guide.
In one implementation, the determining the bending damping and the bending damping interval according to the human body gravity center change feature includes:
determining a falling risk value corresponding to the movement mode according to the gravity center change characteristics of the human body;
and determining the bending damping and the bending damping interval according to the falling risk value.
Specifically, the human body gravity center change characteristics can reflect the requirement of the human body on balance/support in the movement mode, and the possible falling risk of the wearer in the movement mode can be estimated according to the human body gravity center change characteristics, namely the falling risk value is obtained. If the falling risk value is higher, the higher bending damping should be set so that the wearer can obtain more supporting force when the intelligent artificial limb falls to the ground, and falling is prevented. The bending damping and the bending damping interval in this movement mode can thus be set guided by the fall risk value.
In one implementation manner, the initial damping further includes an extension damping, the damping interval further includes an extension damping interval corresponding to the extension damping, and the setting method of the extension damping and the extension damping interval includes:
identifying knee joint points in the skeleton sequence data, and determining knee joint change characteristics according to each identified knee joint point;
And determining the stretching damping and the stretching damping interval according to the knee joint change characteristics.
Specifically, the initial damping preset for different motion modes in this embodiment further includes extension damping, and the function of the extension damping is to control the swing of the intelligent knee joint. The principle of the extension damping of different motion modes and the setting method of the extension damping interval are the same, and one motion mode is taken as an example: firstly, continuously acquiring human body moving images in the moving mode. And then recognizing skeleton parts in each human body moving image through a pre-constructed skeleton recognition algorithm, and generating skeleton sequence data through the recognized skeleton parts under different time steps. And then, identifying knee joint points in the skeleton sequence data, connecting all the identified knee joint points to obtain a second change curve of the knee joint points, and extracting features of the second change curve to obtain knee joint change features. The knee joint change characteristic can reflect the requirement of the human body on flexibility in the movement mode, so that the extension damping and the extension damping interval in the movement mode can be set by taking the knee joint change characteristic as a guide.
In one implementation, the method includes:
Determining a flexibility requirement value corresponding to the movement mode according to the knee joint variation characteristics;
and determining the stretching damping and the stretching damping interval according to the flexibility requirement value.
Specifically, the knee joint change characteristics can reflect the requirement of the human body on flexibility in the movement mode, so that the flexibility requirement value can be estimated according to the knee joint change characteristics. If the flexibility demand is higher, then a lower extension damping should be set so that the wearer can be more flexible in the swing of the intelligent prosthesis. The extension damping and the extension damping interval in this movement mode can thus be set guided by the flexibility requirement.
Step S300, acquiring the movement speed corresponding to the intelligent artificial limb every preset time, and adjusting the current damping in the damping interval according to the movement speed.
Specifically, in order to give a better motion experience to the wearer, the embodiment can dynamically adjust the current damping at regular intervals in the motion process of the wearer, and the specific value of the damping can fluctuate in the damping interval, so that the current motion speed of the wearer is more adapted.
In one implementation, the adjusting the current damping in the damping interval according to the movement speed includes:
Acquiring a reference speed interval corresponding to the movement mode, and judging whether to change the movement mode according to the movement speed and the reference speed interval;
if not, adjusting the current damping in the damping interval according to the movement speed;
if yes, the step of judging the current movement mode of the wearer of the intelligent artificial limb is executed again.
In short, because the damping differences for different movement patterns are large, it is necessary to determine whether the wearer has changed movement patterns before adjusting the damping. Specifically, the present embodiment sets in advance respective corresponding reference velocity intervals for different motion patterns. Whether the wearer changes the movement mode can be confirmed by judging whether the currently detected movement speed is still in the reference speed interval corresponding to the movement mode. If the wearer does not change the movement mode, finely adjusting the current damping according to the current detected movement speed; if the wearer changes the movement pattern, the wearer needs to judge which movement pattern the wearer is currently in again.
In one implementation, if not, adjusting the current damping in the damping interval according to the movement speed includes:
If not, acquiring the historical movement speed recorded in the previous time, and determining the speed change value according to the difference value of the historical movement speed and the movement speed;
and adjusting the current damping in the damping interval according to the speed variation value.
In particular, the difference in the detected movement speeds of two adjacent times may reflect the speed change of the wearer over a corresponding period of time, i.e. the speed change value. The speed change value can be used for judging whether the movement intention of the wearer is deceleration or acceleration or determining the speed change amplitude. The current damping can thus be adjusted within the damping interval based on the speed variation value.
For example, for bending damping, if the wearer is decelerating, the bending damping is adjusted downward within the bending damping interval based on the speed change value; if the wearer is accelerating, the bending damping is adjusted upward in the bending damping interval based on the speed change value. For extension damping, if the wearer is decelerating, up-regulating the extension damping within an extension damping interval based on the speed change value; if the wearer is accelerating, the extension damping is adjusted downward within the extension damping interval based on the speed change value.
In one implementation, the adjusting the current damping in the damping interval according to the speed variation value includes:
determining an adjustment value of the initial damping according to the speed change value, and adjusting the initial damping according to the adjustment value to obtain updated damping;
judging whether the updated damping is positioned in the damping interval or not;
if not, the initial damping is adjusted again according to the extreme value of the damping interval;
if yes, the updated damping is used as the initial damping after adjustment.
Specifically, the amplitude modulation of the initial damping in the damping interval is determined based on the magnitude of the speed variation value, and the larger the speed variation value is, the larger the adjustment value is, and vice versa, the smaller the adjustment value is. Since it is possible that the initial damping exceeds the damping interval after subtracting/adding the adjustment value, the present embodiment defines that the end point value/extreme value of the damping interval is used instead in this case. If the updated damping which is adjusted downwards based on the adjustment value is not in the damping interval, taking the minimum value of the damping interval as the adjusted damping; and if the updated damping after the adjustment value is up-regulated is not in the damping interval, taking the maximum value of the damping interval as the adjusted damping.
For example, regarding the bending damping, if the wearer is decelerating, the bending damping is adjusted downward in the bending damping section based on the speed change value to obtain updated bending damping, and if the updated bending damping is not in the bending damping section, the minimum value of the bending damping section is taken as the adjusted damping; if the wearer is accelerating, the bending damping is adjusted upwards in the bending damping section based on the speed change value to obtain updated bending damping, and if the updated bending damping is not in the bending damping section, the maximum value of the bending damping section is taken as the adjusted damping. For the expansion damping, if the wearer decelerates, the expansion damping is adjusted upwards in an expansion damping interval based on the speed change value to obtain updated expansion damping, and if the updated expansion damping is not in the expansion damping interval, the maximum value of the expansion damping interval is used as adjusted damping; if the wearer is accelerating, the expansion damping is adjusted downwards in the expansion damping interval based on the speed change value to obtain updated expansion damping, and if the updated expansion damping is not in the expansion damping interval, the minimum value of the expansion damping interval is taken as the adjusted damping.
In another implementation manner, if not, adjusting the current damping in the damping interval according to the movement speed includes:
Acquiring a preset corresponding relation curve, wherein the corresponding relation curve is used for reflecting the corresponding relation between the speed and the damping value in the damping interval;
and determining target damping on the corresponding relation curve according to the movement speed, and adjusting the current damping according to the target damping.
Specifically, the present embodiment may preset a corresponding relationship curve of a speed-damping value, where the curve may reflect a fluctuation condition of the damping value along with the speed in the damping interval in the current motion mode. In an actual application scene, the current movement speed is detected, and a corresponding damping value is queried on a corresponding relation curve according to the movement speed, so that the damping value is the target damping adapted to the movement speed in the current movement mode.
Based on the above embodiment, the present invention further provides a damping adjustment device, as shown in fig. 2, including:
the mode judging module 01 is used for judging the current movement mode of the wearer of the intelligent artificial limb;
the damping determining module 02 is used for determining initial damping and damping intervals corresponding to the knee joint of the intelligent artificial limb according to the motion mode;
the damping adjustment module 03 is configured to obtain a movement speed corresponding to the intelligent artificial limb every a preset period of time, and adjust current damping in the damping interval according to the movement speed.
In one implementation, the mode determining module 01 includes:
the conversion unit is used for acquiring detection data of the knee joint of the intelligent artificial limb, converting the detection data into waveform data, and determining periodic distribution rule information corresponding to the detection data according to the waveform data;
the retrieval unit is used for acquiring a motion pattern database, wherein the motion pattern database comprises a plurality of reference motion patterns, and each reference motion pattern is provided with a corresponding periodic distribution rule label;
and the matching unit is used for matching with the motion pattern database according to the periodic distribution rule information and determining the motion pattern according to a matching result.
In one implementation, the initial damping and the damping interval are both preset; the initial damping includes bending damping, the damping interval includes a bending damping interval corresponding to the bending damping, and the device further includes:
the image analysis module is used for acquiring a plurality of human body moving images continuously acquired in the motion mode, and inputting each human body moving image into a skeleton recognition algorithm to obtain skeleton sequence data;
The gravity center identification module is used for identifying the gravity center points of the human body in the skeleton sequence data and determining the gravity center change characteristics of the human body according to the identified gravity center points of the human body;
the first determining module is used for determining the bending damping and the bending damping interval according to the gravity center change characteristics of the human body.
In one implementation, the initial damping further includes an extension damping, the damping interval further includes an extension damping interval corresponding to the extension damping, and the apparatus further includes:
the knee joint identification module is used for identifying knee joint points in the skeleton sequence data and determining knee joint change characteristics according to the identified knee joint points;
and the second determining module is used for determining the stretching damping and the stretching damping interval according to the knee joint change characteristics.
In one implementation, the damping adjustment module 03 includes:
the speed analysis unit is used for acquiring a reference speed interval corresponding to the movement mode and judging whether to change the movement mode according to the movement speed and the reference speed interval;
the damping adjusting unit is used for adjusting the current damping in the damping interval according to the movement speed if not;
And the mode replacing unit is used for re-executing the step of judging the current movement mode of the wearer of the intelligent artificial limb if the intelligent artificial limb is in the current movement mode.
In one implementation, the damping adjustment unit includes:
the record acquisition unit is used for acquiring the historical movement speed recorded in the previous time if not;
a data calculation unit for determining the speed variation value according to the difference between the historical movement speed and the movement speed;
and the damping fine tuning unit is used for adjusting the current damping in the damping interval according to the speed change value.
In one implementation, the damping fine tuning unit includes:
the primary adjusting unit is used for determining an adjusting value of the initial damping according to the speed change value, and adjusting the initial damping according to the adjusting value to obtain updated damping;
the judging unit is used for judging whether the updated damping is positioned in the damping interval;
the final adjusting unit is used for adjusting the initial damping again according to the extreme value of the damping interval if not; if yes, the updated damping is used as the initial damping after adjustment.
In another implementation, the damping adjustment unit includes:
The curve acquisition unit is used for acquiring a preset corresponding relation curve, wherein the corresponding relation curve is used for reflecting the corresponding relation between the speed and the damping value in the damping interval;
and the curve inquiring unit is used for determining target damping on the corresponding relation curve according to the movement speed and adjusting the current damping according to the target damping.
Based on the above embodiments, the present invention also provides a smart prosthesis comprising a knee joint and a damping adjustment device as described in any of the above; the knee joint comprises an angle sensor and an inertial sensor, and the angle sensor and the inertial sensor are used for acquiring detection data of the knee joint.
Specifically, as shown in fig. 3, the intelligent artificial limb of the embodiment comprises a leg main body 4 and a knee joint 2 connected with the leg main body 4 through a rotating shaft, the leg main body is driven to rotate by the rotating shaft, flexible movement of the knee joint 2 is achieved, the knee joint 2 is located at the top of the leg main body 4, the intelligent artificial limb further comprises a receiving cavity 1, the receiving cavity 1 is fixedly connected with the knee joint 2, the receiving cavity 1 is used for being installed on the thigh of a user, a plurality of sensors (including an inertial sensor, an angular inertial sensor and the like) are arranged in the receiving cavity 1, a resistance device 3 is arranged in a cavity in the leg main body 4, and the bottom end of the resistance device 3 is hinged with the leg main body 4. The resistance device 3 of the present embodiment is a hydraulic cylinder, and the resistance device 3 is used for coordinating the movement between the connection portion and the leg main body, and for regulating the relative position between the connection portion and the leg main body. Damping adjustment means may be used to control the resistance means 3.
Based on the above embodiment, the present invention also provides a terminal, and a functional block diagram thereof may be shown in fig. 4. The terminal comprises a processor, a memory, a network interface and a display screen which are connected through a system bus. Wherein the processor of the terminal is adapted to provide computing and control capabilities. The memory of the terminal includes a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface of the terminal is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a damping adjustment method. The display screen of the terminal may be a liquid crystal display screen or an electronic ink display screen.
It will be appreciated by those skilled in the art that the functional block diagram shown in fig. 4 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the terminal to which the present inventive arrangements may be applied, and that a particular terminal may include more or less components than those shown, or may combine some of the components, or have a different arrangement of components.
In one implementation, the memory of the terminal has stored therein one or more programs, and the one or more programs configured to be executed by one or more processors include instructions for performing a damping adjustment method.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
In summary, the invention discloses a damping adjustment method, a damping adjustment device, an intelligent artificial limb, a terminal and a storage medium, wherein the method is used for judging the current movement mode of a wearer of the intelligent artificial limb; determining initial damping and damping intervals corresponding to knee joints of the intelligent artificial limb according to the motion mode; and acquiring the movement speed corresponding to the intelligent artificial limb at intervals of preset time, and adjusting the current damping in the damping interval according to the movement speed. According to the invention, the damping and the damping intervals of different motion modes are preset, and the initial damping and the damping intervals corresponding to the knee joint of the intelligent artificial limb are adjusted based on the motion modes of the wearer in practical application. In the movement process of the wearer, the invention can also adjust the current damping in the damping interval based on the movement speed of the wearer, thereby better meeting the movement requirements of the wearer in different movement modes when wearing the intelligent artificial limb. The intelligent artificial limb damper solves the problem that the damper of the intelligent artificial limb in the prior art adopts preset parameters, and is difficult to adapt to the movement requirements of different movement modes in daily life of a wearer.
It is to be understood that the invention is not limited in its application to the examples described above, but is capable of modification and variation in light of the above teachings by those skilled in the art, and that all such modifications and variations are intended to be included within the scope of the appended claims.
Claims (9)
1. A method of damping adjustment based on a motion pattern, the method comprising:
judging the current movement mode of the wearer of the intelligent artificial limb;
determining initial damping and damping intervals corresponding to knee joints of the intelligent artificial limb according to the motion mode;
acquiring a motion speed corresponding to the intelligent artificial limb at intervals of preset time, and adjusting current damping in the damping interval according to the motion speed;
the judging of the current movement mode of the wearer of the intelligent artificial limb comprises the following steps:
acquiring detection data of the knee joint of the intelligent artificial limb, converting the detection data into waveform data, and determining periodic distribution rule information corresponding to the detection data according to the waveform data;
obtaining a motion pattern database, wherein the motion pattern database comprises a plurality of reference motion patterns, and each reference motion pattern is provided with a corresponding periodic distribution rule label;
matching the periodic distribution rule information with the motion pattern database, and determining the motion pattern according to a matching result;
the initial damping and the damping interval are preset; the initial damping comprises bending damping, the damping interval comprises a bending damping interval corresponding to the bending damping, and the setting method of the bending damping and the bending damping interval comprises the following steps:
Acquiring a plurality of human body moving images continuously acquired in the motion mode, and inputting each human body moving image into a skeleton recognition algorithm to obtain skeleton sequence data;
identifying human body gravity center points in the skeleton sequence data, and determining human body gravity center change characteristics according to the identified human body gravity center points;
determining the bending damping and the bending damping interval according to the gravity center change characteristics of the human body;
the initial damping further comprises an extension damping, the damping section further comprises an extension damping section corresponding to the extension damping, and the setting method of the extension damping and the extension damping section comprises the following steps:
identifying knee joint points in the skeleton sequence data, connecting all the identified knee joint points to obtain a second change curve of the knee joint points, and extracting features of the second change curve to obtain knee joint change features;
and determining a flexibility requirement value corresponding to the movement mode according to the knee joint variation characteristics, and determining the stretching damping and the stretching damping interval according to the flexibility requirement value.
2. The method for adjusting damping based on a motion mode according to claim 1, wherein the adjusting the current damping in the damping interval according to the motion speed includes:
Acquiring a reference speed interval corresponding to the movement mode, and judging whether to change the movement mode according to the movement speed and the reference speed interval;
if not, adjusting the current damping in the damping interval according to the movement speed;
if yes, the step of judging the current movement mode of the wearer of the intelligent artificial limb is executed again.
3. The method for adjusting damping based on a motion mode according to claim 2, wherein if not, adjusting the current damping in the damping interval according to the motion speed comprises:
if not, acquiring the historical movement speed recorded in the previous time, and determining a speed change value according to the difference value of the historical movement speed and the movement speed;
and adjusting the current damping in the damping interval according to the speed variation value.
4. The method for adjusting damping based on a motion mode according to claim 2, wherein if not, adjusting the current damping in the damping interval according to the motion speed comprises:
acquiring a preset corresponding relation curve of the speed and the damping value, wherein the corresponding relation curve is used for reflecting the corresponding relation between the speed and the damping value in the damping interval;
And determining target damping on the corresponding relation curve according to the movement speed, and adjusting the current damping according to the target damping.
5. A motion mode based damping adjustment device, the device comprising:
the mode judging module is used for judging the current movement mode of the wearer of the intelligent artificial limb;
the damping determining module is used for determining initial damping and damping intervals corresponding to the knee joint of the intelligent artificial limb according to the motion mode;
the damping adjustment module is used for acquiring the movement speed corresponding to the intelligent artificial limb at intervals of preset time, and adjusting the current damping in the damping interval according to the movement speed;
the mode judging module includes:
the conversion unit is used for acquiring detection data of the knee joint of the intelligent artificial limb, converting the detection data into waveform data, and determining periodic distribution rule information corresponding to the detection data according to the waveform data;
the retrieval unit is used for acquiring a motion pattern database, wherein the motion pattern database comprises a plurality of reference motion patterns, and each reference motion pattern is provided with a corresponding periodic distribution rule label;
The matching unit is used for matching with the motion pattern database according to the periodic distribution rule information and determining the motion pattern according to a matching result;
the initial damping and the damping interval are preset; the initial damping includes bending damping, the damping interval includes a bending damping interval corresponding to the bending damping, and the device further includes:
the image analysis module is used for acquiring a plurality of human body moving images continuously acquired in the motion mode, and inputting each human body moving image into a skeleton recognition algorithm to obtain skeleton sequence data;
the gravity center identification module is used for identifying the gravity center points of the human body in the skeleton sequence data and determining the gravity center change characteristics of the human body according to the identified gravity center points of the human body;
the first determining module is used for determining the bending damping and the bending damping interval according to the gravity center change characteristics of the human body;
the initial damping further comprises an extension damping, the damping interval further comprises an extension damping interval corresponding to the extension damping, and the device further comprises:
the knee joint identification module is used for identifying knee joint points in the skeleton sequence data, connecting all the identified knee joint points to obtain a second change curve of the knee joint points, and extracting features of the second change curve to obtain knee joint change features;
And the second determining module is used for determining a flexibility requirement value corresponding to the movement mode according to the knee joint change characteristics and determining the stretching damping and the stretching damping interval according to the flexibility requirement value.
6. The motion mode based damping adjustment device of claim 5, wherein the damping adjustment module comprises:
the speed analysis unit is used for acquiring a reference speed interval corresponding to the movement mode and judging whether to change the movement mode according to the movement speed and the reference speed interval;
the damping adjusting unit is used for adjusting the current damping in the damping interval according to the movement speed if not;
and the mode replacing unit is used for re-executing the step of judging the current movement mode of the wearer of the intelligent artificial limb if the intelligent artificial limb is in the current movement mode.
7. A smart prosthesis comprising a knee joint and a motion pattern based damping adjustment device according to any one of claims 5-6; the knee joint comprises an angle sensor and an inertial sensor, and the angle sensor and the inertial sensor are used for acquiring detection data of the knee joint.
8. A terminal comprising a memory and one or more processors; the memory stores more than one program; the program comprising instructions for performing the motion pattern based damping adjustment method according to any one of claims 1-4; the processor is configured to execute the program.
9. A computer readable storage medium having stored thereon a plurality of instructions adapted to be loaded and executed by a processor to implement the steps of the motion pattern based damping adjustment method according to any of the preceding claims 1-4.
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| CN116133620A (en) * | 2020-07-20 | 2023-05-16 | 奥托·博克保健产品有限公司 | Method for controlling a prosthesis or orthosis |
| CN112535474A (en) * | 2020-11-11 | 2021-03-23 | 西安交通大学 | Lower limb movement joint angle real-time prediction method based on similar rule search |
| CN115192049A (en) * | 2022-09-14 | 2022-10-18 | 深圳市心流科技有限公司 | Myoelectricity sampling frequency adjusting method of intelligent artificial limb |
| CN115998494A (en) * | 2023-02-14 | 2023-04-25 | 浙江强脑科技有限公司 | Anti-falling control method and device for intelligent knee joint |
| CN116189383A (en) * | 2023-02-22 | 2023-05-30 | 深圳先进技术研究院 | Fall and similar action early warning method based on inertial sensing |
| CN115969590A (en) * | 2023-03-16 | 2023-04-18 | 深圳市心流科技有限公司 | Knee prosthesis, control method and system, intelligent terminal and storage medium |
| CN116369863A (en) * | 2023-05-08 | 2023-07-04 | 首都医科大学附属北京天坛医院 | Multi-signal information acquisition system based on lower limbs |
| CN117012362A (en) * | 2023-10-07 | 2023-11-07 | 中国康复科学所(中国残联残疾预防与控制研究中心) | Adaptive data identification method, system, equipment and storage medium |
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